1. Joint Modeling
1.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
1.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## HDevsum 1.003 1.003
## LDevsum 1.003 1.008
## dh0 1.002 1.010
## dl0 1.010 1.018
## dl1 0.999 0.999
## dl2 1.013 1.026
## dl3 0.999 0.999
##
## Multivariate psrf
##
## 1
1.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
1.4 WAIC results
| LevelH | LevelL | |
|---|---|---|
| DIC | 1395.53307 | 22691.6689 |
| DIC3 | 1262.92950 | 22378.4486 |
| PWAIC | 95.90693 | 317.4911 |
| WAIC | 1336.23275 | 22414.8555 |
2. Separate Modeling of High-Level
2.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
2.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## HDevsum 1.001 1.006
## dh0 0.999 0.999
##
## Multivariate psrf
##
## 1
2.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
2.4 WAIC results
| H0b | |
|---|---|
| DIC | 1387.17045 |
| DIC3 | 1259.57784 |
| PWAIC | 94.07183 |
| WAIC | 1331.19889 |
3. Separate Modeling for Low-level
3.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
3.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## LDevsum 1.01 1.06
## dl0 1.07 1.27
## dl1 1.02 1.11
## dl2 1.07 1.26
## dl3 1.02 1.09
##
## Multivariate psrf
##
## 1.05
3.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
3.4 WAIC results
| L4 | |
|---|---|
| DIC | 22309.2826 |
| DIC3 | 22301.5691 |
| PWAIC | 314.3169 |
| WAIC | 22337.0302 |